Cohen, A., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel, Division of Agricultural Engineering, Faculty of Civil and Environmental Engineering, Technion -Israel Institute of Technology, Haifa, Israel Cohen, Y., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel Broday, D., Division of Agricultural Engineering, Faculty of Civil and Environmental Engineering, Technion -Israel Institute of Technology, Haifa, Israel Hetzroni, A., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel Alchanatis, V., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel Timar, D., PPMB - Citrus Division, Israel Cohen Institute for Biological Control, Israel Gazit, Y., PPMB - Citrus Division, Israel Cohen Institute for Biological Control, Israel
An initial Spatial Decision Support System (SDSS) for Medfly infestation was developed to improve spraying actions. Beside the spray model that produces a spraying recommendations map, the SDSS has a learning mechanism that aims at realizing the ability of tuning the spray model or indicating data gaps. The learning mechanism compares between the SDSS recommendations and the expert decision and selects appropriate cases for learning. The learning mechanism algorithm is described and initial results are presented. The results indicate a high degree of agreement between the SDSS recommendations and the expert decisions. However, disagreements between the SDSS and the expert decision support the need for such a learning model and indicate ways of tuning the SDSS.
Developing a learning mechanism for a spatial decision support system for medfly control in citrus
Cohen, A., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel, Division of Agricultural Engineering, Faculty of Civil and Environmental Engineering, Technion -Israel Institute of Technology, Haifa, Israel Cohen, Y., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel Broday, D., Division of Agricultural Engineering, Faculty of Civil and Environmental Engineering, Technion -Israel Institute of Technology, Haifa, Israel Hetzroni, A., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel Alchanatis, V., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel Timar, D., PPMB - Citrus Division, Israel Cohen Institute for Biological Control, Israel Gazit, Y., PPMB - Citrus Division, Israel Cohen Institute for Biological Control, Israel
Developing a learning mechanism for a spatial decision support system for medfly control in citrus
An initial Spatial Decision Support System (SDSS) for Medfly infestation was developed to improve spraying actions. Beside the spray model that produces a spraying recommendations map, the SDSS has a learning mechanism that aims at realizing the ability of tuning the spray model or indicating data gaps. The learning mechanism compares between the SDSS recommendations and the expert decision and selects appropriate cases for learning. The learning mechanism algorithm is described and initial results are presented. The results indicate a high degree of agreement between the SDSS recommendations and the expert decisions. However, disagreements between the SDSS and the expert decision support the need for such a learning model and indicate ways of tuning the SDSS.